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Exploiting Views for Collaborative Research Data Management of Structured Data

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From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries (ICADL 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13636))

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Abstract

Data-driven analysis plays a vital role in research projects, and sharing data with collaborators inside or outside a project is supposed to be daily scientific work. There are various tools for research data management, which offer features like storing data, meta-data indexing, and provide options to share data. However, currently, none of them offers capabilities for sharing data in different levels of detail without excessive data duplication. Naturally, sharing data by duplication is a tedious process, as preparing data for sharing typically involves changing temporal resolution (i.e., aggregation) or anonymization, e.g., to ensure privacy. In this paper, instead of re-inventing the wheel, we ask whether the concept of views, a well-established concept in relational databases, fulfills the above requirement. Conducting a case study for a project employing sharing of learning analytics data, we propose a framework that allows for fine-granular configuration of shared content based on the concept of views. In the case study, we a) analyze a data reuse scenario based on the FAIR principles, b) suggest a concept for using views for data sharing, and c) demonstrate its feasibility with a proof-of-concept.

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Notes

  1. 1.

    https://dsgvo-gesetz.de/.

  2. 2.

    https://www.re3data.org/.

  3. 3.

    https://v2.sherpa.ac.uk/opendoar/.

  4. 4.

    https://creativecommons.org/.

  5. 5.

    https://pkp.sfu.ca/ojs/.

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Funding

German Federal Ministry of Education and Research [16DHB 3008].

Author information

Authors and Affiliations

  1. DZHW, Hannover, Germany

    David Broneske

  2. University of Magdeburg, Magdeburg, Germany

    Ian Wolff

  3. Zentral- und Landesbibliothek Berlin, Berlin, Germany

    Veit Köppen

  4. Salzburg University, Salzburg, Austria

    Martin Schäler

Authors
  1. David Broneske
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  2. Ian Wolff
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  3. Veit Köppen
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  4. Martin Schäler
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Corresponding author

Correspondence to David Broneske .

Editor information

Editors and Affiliations

  1. National Taiwan Normal University, Taipei, Taiwan

    Yuen-Hsien Tseng

  2. Doshisha University, Kyoto, Japan

    Marie Katsurai

  3. VNU University of Engineering and Technology, Hanoi, Vietnam

    Hoa N. Nguyen

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Broneske, D., Wolff, I., Köppen, V., Schäler, M. (2022). Exploiting Views for Collaborative Research Data Management of Structured Data. In: Tseng, YH., Katsurai, M., Nguyen, H.N. (eds) From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries. ICADL 2022. Lecture Notes in Computer Science, vol 13636. Springer, Cham. https://doi.org/10.1007/978-3-031-21756-2_28

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  • DOI: https://doi.org/10.1007/978-3-031-21756-2_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21755-5

  • Online ISBN: 978-3-031-21756-2

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